Chain‐routing scheme with compressive sensing‐based data acquisition for Internet of Things‐based wireless sensor networks. Issue 2 (13th January 2021)

• Record Type: Journal Article
• Authors: Aziz, Ahmed; Osamy, Walid; Khedr, Ahmed M.; Salim, Ahmed
• Is Part Of: IET networks. Volume 10:Issue 2(2021)
• Page Start: 43
• Page End: 58
• Publication Date: 2021-01-13
• Subjects: wireless sensor networks -- routing protocols -- data acquisition -- Internet of Things -- compressed sensing -- energy conservation -- telecommunication power management -- energy consumption; Computer network architectures -- Periodicals; Computer network protocols -- Periodicals; Information networks -- Periodicals; Telecommunication systems -- Periodicals; 004.605
• DOI: 10.1049/ntw2.12002
• Languages: English
• ISSNs: 2047-4954

Abstract

Abstract: The emerging Internet of Things (IoT)‐based systems that integrate diverse types of sensors, mobiles and other technologies to physical world is becoming increasingly popular for use in wide varieties of applications. Compressive sensing (CS)‐based information acquisition and in‐network compression provide an effective method for accurate data recovery at the base station (BS) with reduced cost of communication. In this study, how CS can be combined with routing protocols for gathering data in IoT‐based Wireless Sensor Networks (WSNs) in an energy‐efficient manner are examined. A novel chain‐routing scheme with CS based data acquisition is introduced that includes the following new algorithms: (1) Seed Estimation Algorithm (SEA) to find the best measurement matrix by selecting the best‐estimated seed, (2) Chain Construction Algorithm (CCA) to organise the network nodes during transmitting and receiving process, (3) Compression approach with reduced consumption of energy that improves the lifetime of the network by minimising the local data traffic, and (4) Reconstruction Algorithm (RA) that reconstructs the original data with minimum reconstruction error. Here, extensive simulation and analysis results prove the performance of our proposed method in improving the network lifetime 35% better than the ECST algorithm and 93% better than the PEGASIS algorithm. In addition, the proposed reconstruction algorithm exceeds the other reconstruction algorithms performance.